The AI in Business Podcast

Service organizations hold most of their critical expertise in experienced technicians rather than manuals, and that knowledge is leaving as the workforce turns over. In this episode, Thomas Cottereau, CEO and Founder at SightCall, explores why the real challenge is capturing expertise rather than producing more documentation, and how AI can structure what experts already know into trusted knowledge. He outlines how to capture knowledge inside everyday service work, keep human experts reviewing what AI produces, and treat that knowledge as a continuous loop that feeds both technicians and existing AI systems.
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This episode is sponsored by SightCall
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To learn how leading AI brands like NVIDIA and Google Cloud work with Emerj to reach Fortune 500 AI buyers - download our media kit at: emerj.com/AD1

Enterprise investment in AI is rising faster than the ability to prove what it returns, leaving technology and vendor spend largely unexamined until leadership asks whether it is working. In this episode, Kellen Winters, Director of Customer Success and Business Operations for AI at Novartis, examines why demonstrating AI value starts with building a measurement discipline before any tools are chosen. The conversation covers anchoring AI priorities in the processes where work stalls or drains resources, narrowing a long list of use cases to the few that can be measured, tying pilots to existing KPIs within 90 days, and using a structured intake process to track value from the first idea onward.
 
To learn how leading brands and AI startups connect with enterprise AI buyer audiences at scale, download our media kit at emerj.com/AD1

A job title no longer tells you what a technical role actually requires, now that AI has changed how the work gets done.
In this episode, Carrol Chang, CEO of Andela, unpacks how AI is reshaping technical roles, and why hiring and assessment need to shift from job titles to skills.
 
The conversation covers how leaders can assess for judgment and problem-solving rather than just technical output, and how to map a workforce for reskilling as roles continue to change.
 
This episode is sponsored by Andela.
 
To learn the exact strategies we use to help leading AI brands and startups connect with their ideal enterprise AI buyers, visit: emerj.com/AD1

Shifting regulations and siloed risk and compliance functions are forcing enterprise leaders to rethink audit-driven compliance. In this episode, Craig Unger, CEO and Founder at Hyperproof, explains why compliance should be treated as a continuous state, with every control tied back to the organization's overall risk profile. He also covers standardizing a single set of controls across frameworks and regions, expressing risk in financial terms for boards, and using a five-stage maturity model to plan next steps.
 
This episode is sponsored by Hyperproof
 
Learn how leading organizations approach AI investment more like a venture portfolio, and why interdisciplinary collaboration is critical to defining the right data for AI success, download our free PDF report, "Beginning with AI," at emerj.com/aik1

A recommendation that's right 80% of the time sounds fine, until it's steering machinery next to a person. On the factory floor, that margin is the difference between routine and catastrophic. In this episode, Jeff Witt, Global Process Digital Authority at GE Vernova, examines why industrial AI demands a different standard of rigor than its enterprise counterpart, from edge computing architectures to context-rich recommendations frontline workers can trust immediately. He also outlines a framework for earning the right to automate, proving a process is documented, optimized, and consistent before scaling AI across multiple sites.
 
This episode is sponsored by Poka.
 
Learn how to evaluate AI vendors by assessing leadership expertise, and why funding benchmarks can signal product maturity and stability. Download our free PDF report, "5 Ways to Select the Right AI Vendor," at emerj.com/aiv1
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